1. Field of the Invention
The present invention is directed to computer related and/or assisted systems, methods, and computer program devices for group collaboration on projects incorporating all types of electronic information and content. More particularly, the present invention relates to methods and systems for group collaboration where the groups are dynamic and re-definable, where the electronic information and content comprise items that are associatively filed in association with projects, and/or where the group collaboration is integrated with native applications associated with the items.
2. Description of the Related Art
In today's environment, business and user productivity is lost under a growing pile of electronic information. Instead of facilitating decision making and the managing of myriad businesses and transactions, the speed and volume of electronic communication exacerbates the amount of time spent searching for and organizing the information exchanged.
The result has been a growing inability on the part of business personnel, individually and within work groups, and across geographic locations, to organize, access and share this information quickly and efficiently. Failure to access the right information at the right time increases business risk and negatively affects companies' bottom lines.
Electronic information that users need to organize include e-Mail (which can be particularly numerous), documents, spreadsheets, tasks, calendar entries, and various other content. Most of this content is responsive to one native application and not readily accessible via another native application. Moreover, some of this content is “lost” due to inconsistent filing patterns within an organization.
The problem is exacerbated further in particular industries. For example, in financial services, there is often significant transaction risk, and increasingly heightened compliance concerns.
Over the last decade, the financial services industry has spent millions of dollars looking for a solution, such as document and content management, work-flow and knowledge management, and, more recently, corporate portals. These have not adequately addressed users' needs for managing their mission critical information, and therefore have seen limited adoption. Some examples of companies offering such solutions include Documentum, FileNet, Vignette, Stellant, Autonomy, RiskClick, Groove, and Xerox.
Users want to improve the quality of transactions; reduce losses from bad deals, increase revenue by improving efficiency, lower hedging and risk mitigation expenses; and improve customer service and renewal rates. Users want to spend less time looking for deal documents and other critical information. Productivity would improve if information could be shared in real time regardless of location. Moreover, users do not want to change the way they work, and want to keep existing information technology.
A user searching for a necessary document often does not know whether it is on the user's hard drive, in a directory on the network, or perhaps in Outlook attached to a received e-mail message. Furthermore, a user involved in a project or deal needs to know where all documents, messages and other files related to the project or deal are located. Yet another problem is determining where to file a document so that it can be readily located for later use by the same user or others.
Some aspects of conventional systems are illustrated by way of example in FIG. 1, also described in U.S. Pat. No. 6,430,575, Dourish et al. incorporated herein by reference. Dourish provides an example of a prior art collaborative document management system with customizable filing structures. An operating environment 102 is used to define a collaborative document management system that includes a network server 104 accessed by client computers 106 over network 108. A program interface 110 accesses an application program 112, which then incorporates a document store 114 and a filing structure store 116 to provide customizable filing structures. The document store 114 is a shared repository of documents that stores documents independent from the filing structure store 116 that records different categories in which documents 115 in the document store are organized. The filing structure store 116 has defined therein a core filing structure 118 and one or more levels of customized filing structures 120. This category schema is a directory structure that is used to classify the documents 115 in document store 114 so that they can be readily located by a plurality of users. In effect, the category schema is a shared resource that defines the use of the documents categorized thereby. Once a filing structure is defined in the filing structure store 116, documents 115 stored in the document store 114 can be categorized therein. The act of categorizing documents in the filing structure involves the assignment of unique values to one or more predefined document properties (e.g., document filing location). These document properties can be used to individually categorize the collection of documents. After documents are categorized using the category manager 122, the context in which that document was filed can be mapped to other customized filing structures in a manner that is transparent to users operating the application program interfaces. A structure translator 124 computes a mapping between different levels of customization to provide different interpretations of the shared repository of documents.
Another aspect of conventional systems is illustrated in the example of FIG. 2, described in U.S. Pat. No. 6,556,982, McGaffey et al., incorporated herein by reference. McGaffey discloses a prior art data analysis and classification system 200 that operates in two modes: a cognitive (or real-time) processing mode 220 and a learning loop (or non real-time) processing mode 240. The data analysis and classification system performs the steps displayed in the cognitive processing mode 220 directly, while a human expert or team of human experts performs the steps comprising the learning loop 240. The cognitive processing loop 220 comprises four steps. First, the data analysis and classification system reads a dictionary file of all known terms and creates a hash table in step 222. Second, in step 224 the data analysis and classification system reads the list of all relationships and connects them to form the association and classification net (ACN) by applying the relationships, both logical and output to the concepts located within the hash table. In step 224, the data analysis and classification system recognizes three types of logical relationships, e.g., equivalence, implied relationships, etc. Third, the data analysis and classification system reads electronic information and parses it into its component concepts in the electronic information input phase 226. Once the data analysis and classification system has executed the classification phase 228, the data analysis and classification system generates a report 212. Following the report generation, the cognitive processing loop 220 terminates. After the data analysis and classification system has executed the classification phase 228, the data analysis and classification completes the cognitive processing loop 220, the learning loop 240 is entered. In the learning loop 240 a human expert updates the data analysis and classification system's dictionary file and relationship set (the set of all relationships structuring the ACN) in a non-real-time fashion. Initially, an expert reviews an unprocessed terms list 242 (if any) and enter these into the dictionary file in order to insure that all concepts are processed in the future by the cognitive processing loop 220. Once the expert enters any unprocessed concepts into the ACN as part of the unprocessed terms phase 242, he may review the performance of the data analysis and classification system in the expert analysis phase 244. In the expert analysis phase 244, the human expert may critique the performance of the data analysis and classification system by reviewing the report 212. Essentially, the expert double-checks the results generated by the data analysis and classification system, and independently determines whether the report is correct. If the expert agrees with the data analysis and classification system's interpretation result 212 in the expert analysis phase 244, then the learning loop 240 ends. Otherwise, the expert may update the data analysis and classification system in the update phase 246 by instituting new relationships. The data analysis and classification system will apply these new relationships the next time it attempts to process electronic information.
Yet another aspect of conventional systems is described in U.S. Pat. No. 6,014,135, Frenandes, incorporated herein by reference, shown in FIG. 3. Fernandes is an example of a prior art collaboration centric document processing environment. Referring to FIG. 3, there is shown a display 350, which is the output of the monitor, and which interfaces with a user. The display has a plurality of first icons 340 (A-C). Each of the first plurality of icons is a graphical representation of an individual. Each of the first icons 340 has a set of objects, which can be inherited, if the creator of the first icon 340 so desired. Thus, for example, a first icon 340 can be from the Internet published by a user, in which the user has published his desk top view, which can be inherited, by the user of the system. When the user of the system selects the objects associated with the selected first icon 340, which the creator of that first icon 340 has permitted to be published, the user of the system will also see the desk top that the publisher created. As a result, a creator of a first icon with inheritable objects can easily maintain and update objects that are far from the publication location. Moreover, the objects created by the publisher can be inherited in part or in total. Thus, if a publisher has created a first set of objects relating to a desk top, and a second set of objects relating to favorite web sites, a user of the system can choose to inherit one or both types of objects. The display 350 also has a plurality of second icons 342 (A-B), which are graphical representations of information. The information can be of any type. They can include but are not limited to: spread sheet files, text files, images, sound, reference to URL sites on the Internet, etc. Finally, the display 350 has a third icon 344 which is a graphical representation of time. In addition, the display 350 comprises a number of fourth icons 346 (A-F). The fourth icon 346A is the icon of the desktop, which is activated to the display 350. The fourth icon 346B, when activated, is for the creation of documents representing information. The fourth icon 346C, when activated, brings up the display for an inbox containing documents received and sent by the user. The fourth icon 346D, when activated, connects the user to contact various individuals. The fourth icon 346E, when activated, permits printing. Finally, the fourth icon 346F, when activated, undoes the previous action. A number of functions will now be described with regard to the display 350. When the user desires to create a document, the user activates or clicks the fourth icon 346B. The intended document can be an e-mail, text, spreadsheet, database or any other type of input from the user. When the fourth icon 346B is activated, the display 350 changes to show the composition of a document. When the user desires to enter alphanumeric text, an appropriate button is activated and the display 350 is then adapted for entering alphanumeric text for e-mail, HTML creation, word processing or the like. If the user desired to input spreadsheet-type data, a similar button (not shown) would be activated and the screen or display 350 would change into one suitable for spreadsheet data input, including borders for rows and columns.
An example of a conventional method and system for sorting and prioritizing electronic e-mail messages is illustrated in FIG. 4, U.S. Pat. No. 5,377,354, Scannell et al., incorporated herein by reference. Scannell discloses a method and apparatus for prioritizing incoming electronic mail messages 425 for a user using a user created and modified rules-control which is stored in a rules-store 412. Incoming messages 425 are stored in a message store 411 and are screened individually by a rules-test unit 413. The rules-test unit has a comparator 452 which matches keywords chosen by the user while creating the rules, and supplies signals to an action list unit 454. By applying the user created rules for deciding which messages constitute the priority messages for the user, a priority assigning unit 445 within an action portion 435 of the rules-store 412 assigns a priority number (say from 1 to 5, 1 being the highest priority for example) to each screened message. Responsive to the assigned priority number of the screened message, the message is sent to a main folder store or forwarded or put away as appropriate. The user created rules can be modified by the user using a conventional keyboard.
The above prior art references and other conventional systems, however, fail to meet the needs of various industries to efficiently search for and organize the ever-increasing amount of electronic information needed to conduct their businesses, including, for example, e-Mail (which can be particularly numerous); documents, spreadsheets, tasks, calendar entries, and various other content. Furthermore, conventional systems do not sufficiently provide for work group collaboration, e.g., where the groups are dynamic and re-definable. Moreover, none of these conventional systems provide for content made available from different applications. Users are still looking for a solution to provide the right information at the right time and to manage all types of information, from daily e-mail to mission critical data.